Dropout In Higher Education Research Articles

Risk factors for student dropout in higher education institutions in latin america

Introduction: In Latin America, university dropouts significantly influence the individual development of students and the socioeconomic progress of the region. Identifying risk factors allows educational institutions to recognize and address the specific needs of their students to create effective methods that foster academic success and retention. Objective: Analyze the various risk factors for student Dropout in Higher Education Institutions in Latin America with the purpose of proposing strategies that reduce the negative rates of this problem. Methods: A bibliographic review of studies published between 2010 and 2024 on risk factors for student dropout in higher education in Latin America was carried out, using relevant databases and applying rigorous inclusion and exclusion criteria. Results: Personal, academic, institutional and socioeconomic variables are part of the risk factors for University Dropout. The lack of access to Higher Education has a significant impact on the economic and social growth of Latin America since it is essential for the training of qualified professionals. The high dropout rate contributes to a less prepared workforce and limits job opportunities for young people. Conclusions: The prevalent risk factors were academic and personal associated with university dropout in Latin America, which is why various strategies were proposed to generate inclusive and equitable higher education through the reformulation of public and institutional policies.

Causes of Dropout in Higher Education: An Analysis of Student Dropouts in Bachelor of Education from Marsyangdi Multiple Campus

Student dropout in higher education institutions (HEIs) is a serious problem in many developed and developing countries including Nepal. According to the University Grants Commission (UGC) report, many campuses are at risk and have a few number of students due to the high dropout rate. This paper aims to analyse student dropout in B.Ed. programme at Marsyangdi Multiple Campus (MMC) and explores the main causes of high dropouts with some measuring strategies to mitigate the problem. Following a quantitative survey through telephone interviews with 30 dropout students, I collected information and analysed it thematically in a narrative way. The findings of the study revealed that 65.47% of students left the campus before completing their degree. The study explored the major causes of high dropouts related to four indicators such as student, institutional, family, and community. Most of the students left their studies due to financial constraints, socioeconomic factors, institutional insufficiency, employment opportunities, study abroad, and early marriage and early pregnancy. The findings of the study apply to reducing the increasing number of dropouts from the university and other similar campuses. In addition to this, it implies formulating higher education policy and reforming the HEIs as per the demands of the time.

Relevant factors and the student profile that result in dropout in higher education: A case study at the Federal Institute of Espírito Santo campus Itapina

School dropout consists of the definitive departure of the student without completing his or her original course. This work aimed to discuss reasons that led students between the years 2014 and 2016 to drop out of the higher education course of Agricultural Sciences at the Federal Institute of Espírito Santo. This research focused on investigating possible reasons for dropout that may be internal, that is, linked to the institution or linked to the personal situations of former students. Exploratory research of a qualitative nature was chosen, using tools for data collection and analysis quantitatively and qualitatively, in addition to the methodology of participatory observation. In the technical procedures, a questionnaire with objective questions was applied, based on a questionnaire used to measure the dropout of students from the institution. According to the answers obtained, it was inferred that the main reasons that led the students to drop out were the lack of recognition of the teaching profession, dissatisfaction with the contents and chosen course, dissatisfaction with their own academic performance, among others. It is necessary to emphasize that some of the above-mentioned answers disagree when taking into account that the highest dropout rates occur in the first semesters, showing that little persistence or support for the student in permanence in the course can also be a determining factor.

Higher Education Dropout: A Scoping Review

Higher Education Dropout: A Scoping Review

Analyzing the Abandonment Rates in Romanian HEIs

Abstract The advancement of technology, the changing and competitive business environment has an impact also on higher education. Potential students are faced with a multitude of choices, without always having the proper guidance to choose a path that is suitable for each of them. Their sometimes-uninformed decision, along with other factors may lead to the phenomenon of dropout. This has a negative impact on universities environment in terms of programs, to society and economy, all being linked in a way. The issue of dropout in higher education is a complex one, a challenging one these days and therefore research on this subject to address it properly are essential. In this article it is presented the current situation on Romanian universities and their dropout rates. Also, an analysis of scientific papers and sources is carried out to identify and document the key factors that contribute to the student’s choice of abandoning their university studies.

Minority Dropouts in Higher Education: The Influence of Family Factors

According to existing literature, familial support has been shown to be a significant predictor of students’ success or failure in school. In this paper, we investigate family-related factors that contribute to minority students dropping out. A qualitative research approach was employed in this study, which involved 11 Hmong studentleavers as key interviewees. Participants were asked about their university education experiences and why they discontinued their studies. The data obtained from interviews were analyzed through qualitative content analysis. As the findings of the study indicate, four family-related factors were most prevalent in causing minority students to withdraw from their studies: family economic situation, parental attitudes, marriage/early parenthood, and home life situations. Future research in this area is strongly recommended.

Transformative Learning Transforming Research

Two research projects undertaken ten years ago explored the experiences of mature students’ access, progression and drop-out in higher education, relying on Habermas and Honneth for sensitizing concepts. This paper explores the implications of undertaking this research today adopting a different set of sensitizing concepts and in the process transforming the identity of the researcher. To this end, this paper moves beyond Habermas and Honneth to the critical theory of Negt and Kluge as a source of new sensitizing concepts informing a reimagined researcher and research project. Their work on experience, its dialectic nature, imploitation, obstinacy – as an alternative to resilience – and a sociological imagination are explored in order to identify possible new sensitizing concepts for researching adults returning to higher education. Implications for transformative adult education will be identified.

Dropout in Andalusian universities: prediction and prevention

Problem and objectiveUniversity dropout is a major problem that affects more than 31,000 students each year in Andalusian universities, with serious personal and social consequences and an economic cost of more than 222 million euros for the region’s public administration. As concluded from the review of explanatory models we reviewed, dropout has a multicausal origin. The purpose of our work is to test the efficacy of the use of a screening for the early detection of the risk of academic dropout in Higher Education in Andalusian universities.ProcedureWe applied a screening instrument adapted for incoming students in public universities in Andalusia. The survey was applied at the beginning of the second semester. In this article we present data from a sample composed of 976 subjects from the universities of Granada UGR, Jaén UJA and Pablo de Olavide de Sevilla UPO.ResultsWith the data obtained we have established the dropout risk group, which includes those students who do not reach an average score of 3.00 in the total screening. There are 34 students representing 3.48% of the sample. Of these 34 students, 26 are women and 8 are men; 20 belong to the UGR, 8 to the UJA and 5 to the UPO. The detection of the risk group will allow the universities to apply preventive measures in a personalized and adjusted way to avoid possible dropout.

What Works? Interventions Aimed at Reducing Student Dropout in Higher Education

What Works? Interventions Aimed at Reducing Student Dropout in Higher Education

Undergraduate Dropout Intentions in Turkey: A Systematic Review of Factors and Implications

The purpose of this research is to find and analyze the sources about student dropout in higher education in Turkey using the systematic review method. According to the research questions, sixteen sources (nine papers and seven theses in the year 2012 and after) conducted in Turkey are taken into consideration and make a content base analysis defined under the PRISMA 2020 Method. The qualitative and quantitative methods were used to examine the problems more deeply and to indicate the factors behind the problems. The samples were composed of people still in the university, people who dropped out of the university, instructors, and administrators. The factors behind dropout are taken in two processes as pre-university (personal factors, the effects of guidance to choose a department, family factors, educational system-related factors, the level of vocational maturity factors, and the factors of the location city of the university) and university (social adaptation, academic factors, and organizational factors). In this study, the causes and consequences of school dropouts, and solutions to prevent or reduce dropouts were discussed.

Application of the Learning Vector Quantization Algorithm for Classification of Students with the Potential to Drop Out

Universities, as providers of academic education services, are required to provide an optimal educational process for students to produce a generation of quality human beings. Student learning success is seen as the success of universities in implementing the higher education process. One of the problems universities face in maintaining the quality of education is student dropout. The high dropout rate in universities can impact accreditation assessments. As a result, it will affect the level of public trust. The number of dropouts in higher education can be minimized from an early age by analyzing the factors that cause student dropouts using data on students who graduated and those who dropped out. This data can be used to determine student dropout patterns by classifying them using the artificial neural network learning vector quantization (LVQ) approach. The data used in this research was 4053, consisting of 3840 graduate student data and 213 dropout student data. This data is considered unbalanced, an unbalanced dataset can cause errors because the model tends to classify the majority class with a high classification and pays less attention to the minority class. So, it is necessary to apply oversampling techniques to overcome this problem. The research results show that the application of the LVQ method to unbalanced data produces an accuracy value of 95.53%, a precision value of 100%, a recall value of 15.02% and an f1-score of 0.26, while the application of the LVQ method to data that has undergone resampling resulting in an accuracy value of 94.66%, a precision value of 92.22%, a recall value of 97.55%, and an f1-score value of 0.95. The LVQ method can be used to classify dropout students with excellent results.

Predicting dropout in Higher Education across borders

ABSTRACT Study success in Higher Education is of primary importance in the European policy agenda. Yet, given the diverse educational landscape across countries and institutions, more coordinated action is needed to gain a more solid knowledge of the dropout phenomenon. This study aims to gain a better insight into students’ dropout based on an integrated comparative study of two universities located in two different European countries: Politecnico di Milano (Italy) and Vrije Universiteit Amsterdam (the Netherlands). This research aims at assessing whether the factors affecting dropout are similar in the Italian and the Dutch contexts by testing the predictive capacity of ad-hoc models trained in other university-country settings at three different stages of the student’s university journey: (i) enrolment, (ii) end of the first semester, and (iii) end of the first year. Results show that the predictive capacity of models is exchangeable across different contexts, and it improves dramatically once data on university performance becomes available. We find that the models trained in the Dutch context have a better ability to identify dropouts in the Italian context than the other way around. Models trained on Dutch data allow us to better understand the relationship between educational credits obtained, the most important variable across models, and students’ dropout. This study contributes to creating a European common arena for discussing Higher Education success issues.

First-year seminars through the lens of Vincent Tinto's theories of student departure. A systematic review

IntroductionVincent Tinto is a towering figure in the study of dropout in higher education whose theory regarding student departure is a widely accepted contribution that explains how students become involved in the academic community and how their level of engagement impacts their decision to persist or to drop out. The aim of this study is to advance understanding of how Vincent Tinto's theories influence the current practices and support services offered by higher education institutions to freshman students through first-year seminars (FYS).MethodsA systematic review was conducted based on peer-reviewed articles published between 2020 and 2022, selected through a multi-stage process. With reference to Tinto's contribution, this systematic review aims at providing answers to the following research questions: What are the methodological approaches identified in the studies under analysis? What knowledge can be identified in recent studies related to the categories of students attending FYS? What knowledge about students' personal and psychological characteristics with relevance for FYS can be found in recent studies? What knowledge about academic pedagogical and counseling factors with relevance for FYS can be found in recent studies? What knowledge about social and relational factors integration with relevance for FYS can be found in recent studies?ResultsThe findings indicate three categories of studies that capitalize on Tinto's theories with regard to the design, conduct and evaluation of first-year seminars: a. studies that assess the role of students' personal and psychological variables, considered within FYS; b. studies that analyze the pedagogical and counseling interventions destined to students within FYS; c. studies that analyze the role of the social and relational dimension within FYS.DiscussionThe literature on the topic capitalizes on Vincent Tinto's contributions in relation to a student corpus which is extremely diverse in terms of age, socio-economic status, racial and cultural characteristics, attended specialization (a significant number of studies are destined to students who attend STEM specializations), generational characteristics (the example of first-generation students). Therefore, the interventions aimed at facilitating the integration of first-year students are carefully tailored and customized according to the needs of these categories of beneficiaries.

Prevention and Mitigation of Rural Higher Education Dropout in Colombia: A Dynamic Performance Management Approach.

Background: Dropout in higher education is a socio-educational phenomenon that has the scope to limit the benefits of education as well as to widen social disparities. For this reason, governments have implemented various public policies for its prevention and mitigation. However, in rural populations, such policies have proven to be ineffective. The aim of this paper is to simulate public policy scenarios for the treatment of school dropout in rural higher education in Colombia from a Dynamic Performance Management approach. Methodology: To achieve the aim, a parameterised simulation model was designed with data from Colombian state entities in rural higher education. Five simulations were carried out. The analysis of the results was carried out using descriptive statistics and comparison of means using the Wilcoxon Sign Rank statistic. Results: The adoption of such an approach based on simulations suggests that policies to expand the coverage of educational credits and financial support, as well as the addition of a family income subsidy, allow for a reduction in the number of dropouts. Conclusions: A dynamic, data-driven approach can be effective in preventing and mitigating dropout in these areas. It also highlights the importance of identifying the key factors contributing to dropout. The results also suggest that government policies can have a significant impact on school retention in rural areas.

Uluslararası öğrencilerin üniversiteye uyum süreçleri bağlamında okulu bırakma eğilimlerinin incelenmesi

Internationalization in higher education has gained importance across the world because it provides opportunities for interaction and development in many fields. While universities endeavor to be preferred by international students, the adaptation processes of students have become a current issue. The problems experienced by international students in the process of adapting is an issue that should be emphasized because it can play a role in school dropout. In this study, adaptation processes of international students in the education faculty of a public university in Turkey and the relationship between adaptation and the tendency of students to dropout were examined. Eight international students participated to this qualitative research, which was carried out with a phenomenological design. Participants were from Afghanistan, Syria, Turkmenistan, Pakistan, Uganda. The data were collected with a semi-structured interview form developed by researchers and analyzed with descriptive analysis. In the study, the reasons for studying abroad and the adaptation processes of the participants in seven themes, and their opinions on dropping out of university education were examined. According to the results of research, most of the participants of this study stated that they have thought dropping out the university. When the reasons that make them think dropping out are evaluated, academic adaptation and cultural harmony was the most important dimensions. Based on this, it can be said that it is necessary to give importance to the academic and cultural adaptation of international students in order to prevent their school dropout in higher education.

The deficient factual basis of the main explanatory models of dropout in higher education

In the last 40 years in much of the western world dropout rates in higher education have remained almost unchanged. Although student retention seems to be the most studied and discussed aspect, nearly every empirical study on the causes of dropout in higher education and even more the impact of retention actions carried out by universities, in most cases have achieved modest results. This paper argues that this fact finds its explanation, to a certain extent, in the nature of the methodological approaches and factual supports of the empirical studies that most of those actions were based on. In this regard, there are strong arguments and empirical evidence that reveal the deficient nature of the factual basis of the most accepted models, theorizations and measurements on dropout in higher education. Among them are those that underlie the models proposed in 2012 by Vincent Tinto and Adam Seidman, the two main current references on the subject. The most significant questions point to the low reliability of the inferences produced from the application of surveys, especially the national survey of student engagement, very recurrently applied throughout the western world in empirical studies on dropout in higher education.

Multi-Class Phased Prediction of Academic Performance and Dropout in Higher Education

The application of intelligent systems in the higher education sector is an active field of research, powered by the abundance of available data and by the urgency to define effective, data-driven strategies to overcome students’ dropout and improve students’ academic performance. This work applies machine learning techniques to develop prediction models that can contribute to the early detection of students at risk of dropping out or not finishing their degree in due time. It also evaluates the best moment for performing the prediction along the student’s enrollment year. The models are built on data of undergraduate students from a Polytechnic University in Portugal, enrolled between 2009 and 2017, comprising academic, social–demographic, and macroeconomic information at three different phases during the first academic year of the students. Five machine learning algorithms are used to train prediction models at each phase, and the most relevant features for the top performing models are identified. Results show that the best models use Random Forest, either incorporating strategies to deal with the imbalanced nature of the data or using such strategies at the data level. The best results are obtained at the end of the first semester, when some information about the academic performance after enrollment is already available. The overall results compare fairly with some similar works that address the early prediction of students’ dropout or academic performance.

Causes of academic dropout in higher education in Andalusia and proposals for its prevention at university: A systematic review

IntroductionOne of the main problems facing the university system is the high student dropout rate due to a number of variables, accentuated by the COVID-19 pandemic. This is a problem not only in Spanish universities but is prevalent worldwide. It is therefore important to understand and analyze the underlying reasons for dropout so that it can be addressed and mechanisms implemented to limit dropout in higher education to the greatest extent possible.MethodA systematic review was carried out summarizing the results of studies and reports on university dropout in Spain and specifically in the universities of the Autonomous Community of Andalusia. The review was conducted in accordance with the PRISMA statement by searching the scientific databases Scopus and Web of Science, limiting the search to articles published between 2010 and 2022.ResultsThe main publications in both Spain and the Autonomous Community of Andalusia were identified. The review included the main causes of university dropout indicated in each of the selected studies and the proposals to reduce it, including educational policies, the rise of distance education, academic failure in basic educational stages, and social, personal, psychological, and economic variables.ConclusionThere is a lack of research on university dropout, with only 25% of Spanish universities having carried out research on this subject in the last 12 years. The studies analyzed conclude that the most frequent causes of university dropout are associated with low academic performance, poor social support in the new academic environment, low socio-economic status, pessimism, and lack of motivation, together with other less significant factors such as poor relationships with teachers, lack of vocation, work incompatibility, and previous academic performance. Further research on the causes of university dropout and its prevention is needed both before university entrance, by providing meaningful information to secondary school students, and during the university stay, through institutional and teaching policies that improve family support and social roots, produce positive academic experiences, favor associationism, and encourage activities that improve planning and time management, together with cognitive learning strategies, motivational strategies and the use of advanced learning materials [such as Information and Communication Technology (ICT) tools].

Student Academic and Social Engagement in the Life of the Academy—A Lever for Retention and Persistence in Higher Education

Research studies worldwide have focused on higher education dropout, persistence, and success. Given the profound changes in higher education that have taken place in recent decades, higher education institutions need to compete for students by attracting, retaining, and, ultimately, graduating them. Thus, higher education institutions increasingly offer actions that aim to foster student success. While a smooth and supported process of student transition from secondary to tertiary education is one of the key variables in higher education student retention and paramount for preventing student dropout, the student’s overall experience in higher education plays a pivotal role in their performance and success. This paper focuses specifically on higher education students’ academic and social involvement, notably through their engagement in extracurricular activities and decision-making processes, which are perceived as critical mechanisms in their persistence in higher education. The study used a qualitative approach with the analysis of four Portuguese higher education institutions. Data were collected through in-depth interviews with students and institutional leaders, complemented with document analysis, and explored through content analysis. The results reveal that, from the wide range of opportunities for involvement offered to students by the higher education institution, activities of an academic nature are the most sought after by students to complement their educational experience. However, students perceive involvement in extracurricular activities in general as critical, both to their overall education and preparation for the labor market and to an easier integration into the institutional environment. Hence, student involvement in cultural or recreational activities, alongside their involvement in institutional decision-making bodies and associative movements, is a privileged way of complementing students’ academic training and is perceived by them as important in their overall education, both as professionals and as individuals.

A decision support framework to incorporate textual data for early student dropout prediction in higher education

Managing student dropout in higher education is critical, considering its substantial impacts on students' lives, academic institutions, and society as a whole. Using predictive modeling can be instrumental for this task, as a means to identify dropouts proactively on the basis of student characteristics and their academic performance. To enhance these predictions, textual student feedback also might be relevant; this article proposes a hybrid decision support framework that combines predictive modeling with student segmentation efforts. A real-life data set from a French higher education institution, containing information of 14,391 students and 62,545 feedback documents, confirms the superior performance of the proposed framework, in terms of the area under the curve and top decile lift, compared with various benchmarks. In contributing to decision support system research, this study (1) proposes a new framework for automatic, data-driven segmentation of students based on textual data; (2) compares multiple text representation methods and confirms that incorporating student textual feedback data improves the predictive performance of student dropout models; and (3) establishes useful insights to help decision-makers anticipate and manage student dropout behaviors.